Combining binary constraint networks in qualitative reasoning

Publisher:
IOS Press
Publication Type:
Conference Proceeding
Citation:
Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence: Frontiers in Artificial Intelligence and Applications, 2008, 178 pp. 515 - 519
Issue Date:
2008-01
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Constraint networks in qualitative spatial and temporal reasoning are always complete graphs. When one adds an extra element to a given network, previously unknown constraints are derived by intersections and compositions of other constraints, and this may introduce inconsistency to the overall network. Likewise, when combining two consistent networks that share a common part, the combined network may become inconsistent. In this paper, we analyse the problem of combining these binary constraint networks and develop certain conditions to ensure combining two networks will never introduce an inconsistency for a given spatial or temporal calculus. This enables us to maintain a consistent world-view while acquiring new information in relation with some part of it. In addition, our results enable us to prove other important properties of qualitative spatial and temporal calculi in areas such as representability and complexity.
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